Extended Data Fig. 8: Exponential fits for different subsampled recording durations.

Black lines indicate the mean across units of the neural similarity as a function of time difference for units recorded for at least 14 days during the lever-pressing task (c.f. Fig. 4c). We fitted exponential models to the mean data, considering only data up to and including increasing time differences (legend). As the subsampled ‘recording duration’ increases, so does the stability index learned in the exponential model for both neurons recorded in DLS (a) and MC (b). If the observed increase in stability with recording duration is due to latent processes with autocorrelations on the order of days, we would expect the neural similarity to decrease to some saturating baseline value, γ. We therefore also fitted a model to the average similarity across neurons as a function of time difference, which assumes a decay to such a baseline (\(\rho = \beta e^{\alpha \,\delta t} + \gamma\); red dashed lines). This model yielded an asymptotic correlation of γ = 0.71 for DLS and γ = 0.58 for MC, suggesting a high degree of neural similarity at long timescales.